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Species interactions shape the diversity and resilience of ecological networks. Plant and animal traits, as well as phylogeny, affect interaction likelihood, driving variation in network structure and tolerance to disturbance. We investigated how traits and phylogenetic effects influenced network-wide interaction probabilities and examined the consequences of extinction on the structure and robustness of ecological networks. We combined both mutualistic and antagonistic interactions of animals (55 species, Infraorder Lemuriformes, Order Primates) and their food plants (590 genera) throughout Madagascar to generate ecological networks. We tested the effects of both lemur and plant traits, biogeographic factors, and phylogenetic relatedness on interaction probability in these networks using exponential random graph models. Next, we simulated animal and plant extinction to analyze the effects of extinction on network structure (connectance, nestedness, and modularity) and robustness for mutualistic, antagonistic, and combined plant-animal networks. Both animal and plant traits affected their interaction probabilities. Large, frugivorous lemurs with a short gestation length, occurring in arid habitats, and with a Least Concern threat level had a high interaction probability in the network, given all other variables. Closely related plants were more likely to interact with the same lemur species than distantly related plants, but closely related lemurs were not more likely to interact with the same plant genus. Simulated lemur extinction tended to increase connectance and modularity, but decrease nestedness and robustness, compared to pre-extinction networks. Networks were more tolerant to plant than lemur extinctions. 5. Lemur-plant interactions were highly trait-structured and the loss of both lemurs and plants threatened the tolerance of mutualistic, antagonistic, and combined networks to future disturbance.

Food web models parameterised using body size show promise to predict trophic interaction strengths (IS) and abundance dynamics. However, this remains to be rigorously tested in food webs beyond simple trophic modules, where indirect and intraguild interactions could be important and driven by traits other than body size. We systematically varied predator body size, guild composition and richness in microcosm insect webs and compared experimental outcomes with predictions of IS from models with allometrically scaled parameters. Body size was a strong predictor of IS in simple modules (r(2)=0.92), but with increasing complexity the predictive power decreased, with model IS being consistently overestimated. We quantify the strength of observed trophic interaction modifications, partition this into density-mediated vs. behaviour-mediated indirect effects and show that model shortcomings in predicting IS is related to the size of behaviour-mediated effects. Our findings encourage development of dynamical food web models explicitly including and exploring indirect mechanisms. CC BY 4.0

Consumer–resource interactions are often influenced by other species in the community. At present these ‘trophic interaction modifications’ are rarely included in ecological models despite demonstrations that they can drive system dynamics. Here, we advocate and extend an approach that has the potential to unite and represent this key group of non‐trophic interactions by emphasising the change to trophic interactions induced by modifying species. We highlight the opportunities this approach brings in comparison to frameworks that coerce trophic interaction modifications into pairwise relationships. To establish common frames of reference and explore the value of the approach, we set out a range of metrics for the ‘strength’ of an interaction modification which incorporate increasing levels of contextual information about the system. Through demonstrations in three‐species model systems, we establish that these metrics capture complimentary aspects of interaction modifications. We show how the approach can be used in a range of empirical contexts; we identify as specific gaps in current understanding experiments with multiple levels of modifier species and the distributions of modifications in networks. The trophic interaction modification approach we propose can motivate and unite empirical and theoretical studies of system dynamics, providing a route to confront ecological complexity.